Agent skill · AI & Agents

monte-carlo-engine

Monte Carlo simulation engine skill for probabilistic modeling, risk quantification, and uncertainty propagation

a5c-ai1,642★ · 1 repos on radarProfile →
claude-codecodexcan modify filesMIT
Install
npx skills add a5c-ai/babysitter --skill monte-carlo-engine --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Allowed tools: -Read-Write-Glob-Grep-Bash
Path: library/specializations/domains/business/decision-intelligence/skills/monte-carlo-engine/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,642
Language: JavaScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Monte Carlo Engine ## Overview The Monte Carlo Engine skill provides comprehensive probabilistic simulation capabilities for quantifying uncertainty, assessing risk, and propagating variability through complex models. It supports multiple sampling strategies, correlation handling, and statistical analysis of simulation outputs for data-driven decision support. ## Capabilities - Random variate generation (normal, triangular, PERT, uniform, lognormal, beta, etc.) - Latin Hypercube Sampling (LHS) - Correlation structure handling (Cholesky decomposition, copulas) - Convergence monitoring and adaptive iteration - Statistical output analysis (mean, variance, percentiles) - Tornado diagram generation - Value at Risk (VaR) and CVaR calculation - Parallel simulation execution ## Used By Processes - Monte Carlo Simulation for Decision Support - Strategic Scenario Development - What-If Analysis Framework - Predictive Analytics Implementation ## Usage ### Distribution Specification ```python # Define input distributions input_variables = { "revenue": { "distribution": "triangular", "parameters": {"min": 800000, "mode": 1000000, "max": 1500000} }, "cost": { "distribution": "normal", "paramete

What's inside
Steps it walks through
  1. Overview
  2. Capabilities
  3. Used By Processes
  4. Usage
  5. Distribution Specification
  6. Correlation Matrix
  7. Model Function
  8. Sampling Strategies
  9. Convergence Monitoring
  10. Input Schema
  11. Output Schema
  12. Best Practices
  13. Integration Points
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About this skill
What does the monte-carlo-engine skill do?

Monte Carlo simulation engine skill for probabilistic modeling, risk quantification, and uncertainty propagation

How do I install it?

Run `npx skills add a5c-ai/babysitter --skill monte-carlo-engine --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going